Search results for "GiST"

showing 10 items of 3463 documents

Effects of ocean acidification on embryonic respiration and development of a temperate wrasse living along a natural CO2 gradient

2016

Volcanic CO2 seeps provide opportunities to investigate the effects of ocean acidification on organisms in the wild. To understand the influence of increasing CO2 concentrations on the metabolic rate (oxygen consumption) and the development of ocellated wrasse early life stages, we ran two field experiments, collecting embryos from nesting sites with different partial pressures of CO2 [pCO2; ambient (400 µatm) and high (800-1000 µatm)] and reciprocally transplanting embryos from ambient- to high-CO2 sites for 30 h. Ocellated wrasse offspring brooded in different CO2 conditions had similar responses, but after transplanting portions of nests to the high-CO2 site, embryos from parents that sp…

StageOcean Acidification International Coordination Centre (OA-ICC)TemperateRegistration number of speciesSalinityinorganicYolk area standard errorAlkalinityExperimentTemperature waterCarbon inorganic dissolvedCalculated using seacarb after Nisumaa et al 2010Aragonite saturation stateRespiration rate oxygenChordataAlkalinity totaltotalCO2 ventpHPelagosReproductionRespirationSymphodus ocellatusTemperatureYolk areadissolvedCarbonate ionPartial pressure of carbon dioxide (water) at sea surface temperature (wet air)Field experimentTemperature water standard deviationTime pointstandard errorRespiration rateEarth System Researchstandard deviationFOS: Medical biotechnologyUniform resource locator link to referenceTime point descriptiveHatchling lengthCalcite saturation statewaterPartial pressure of carbon dioxidedescriptiveGrowth MorphologyFigureUniform resource locator/link to referenceSalinity standard deviationOcean Acidification International Coordination Centre OA ICCMediterranean SeaAnimaliaEggs areaTypeBicarbonate ionNektonEggs area standard errorCalculated using seacarb after Nisumaa et al. (2010)SpeciesPartial pressure of carbon dioxide standard deviationCarbonate system computation flagpH standard deviationHatchling length standard errorFugacity of carbon dioxide (water) at sea surface temperature (wet air)CarbonTreatmentOxygenPartial pressure of carbon dioxide water at sea surface temperature wet airCarbon dioxideGrowth/MorphologySingle speciesOxygen standard deviationFugacity of carbon dioxide water at sea surface temperature wet airCoast and continental shelf
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Cyclic Dynamic Evaluation of Logistics Services Stakeholders Based on System with OFN Model

2021

The challenge for enterprises and supply chains is to deliver successful logistics services in compliance with their aims. Logistics services are affected by many stakeholders. Recognizing their impact on the undertaken services is important for the planning and execution of a sufficiently rigorous stakeholder management process. The aim of the paper is to present a new approach to the analysis of stakeholders - cyclic dynamic evaluation, which could be used in service management, such as in logistics services. We present a novel fuzzy inference system based on the mathematical apparatus of Ordered Fuzzy Numbers (OFNs). The evaluation of stakeholders consists in assessing key factors as - f…

StakeholdersInferenceFuzzy systemOrdered fuzzy numberFuzzy setProjectFuzzy logiLogistics servicesSupply chain
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Use of Logistic Regression for Prediction of the Fate of Staphylococcus aureus in Pasteurized Milk in the Presence of Two Lytic Phages

2010

The use of bacteriophages provides an attractive approach to the fight against food-borne pathogenic bacteria, since they can be found in different environments and are unable to infect humans, both characteristics of which support their use as biocontrol agents. Two lytic bacteriophages, vB_SauS-phiIPLA35 (phiIPLA35) and vB_SauS-phiIPLA88 (phiIPLA88), previously isolated from the dairy environment inhibited the growth of Staphylococcus aureus. To facilitate the successful application of both bacteriophages as biocontrol agents, probabilistic models for predicting S. aureus inactivation by the phages in pasteurized milk were developed. A linear logistic regression procedure was used to desc…

Staphylococcus aureusMicrococcaceaeTime Factorsmedicine.disease_causeApplied Microbiology and BiotechnologyLyticMicrobiologyBacteriophagePredictive Value of TestsPasteurized milkmedicineAnimalsBacteriophagesPest Control BiologicalEcologybiologyTemperaturePathogenic bacteriaContaminationbiology.organism_classificationTiterLogistic ModelsMilkLytic cycleStaphylococcus aureusFood MicrobiologyPhagesPredictionBacteriaFood ScienceBiotechnology
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The effect of an eco-label on the booking decisions of air passengers

2022

Abstract In the last few years there has been an increasing attempt to find solutions on how to mitigate the environmental impacts of air travel. Behavioral change has hereby been identified as the measure with the most significant impact. One way to encourage behavioral change is the use of eco-labels. Eco-labels have, to date, received scant attention in the aviation industry, and their effect on air travel behavior is still largely unknown. This study explores the effect of an eco-label on the booking decisions of passengers. We conduct a stated choice experiment with 553 air passengers. Our findings show that providing passengers with an eco-label leads to behavioral change, as the labe…

Stated choice050210 logistics & transportationAviationbusiness.industry05 social sciencesGeography Planning and Development0211 other engineering and technologiesTransportation02 engineering and technologyEnvironmentally friendlyPreferenceWillingness to pay0502 economics and business021108 energyMarketingbusinessAir travelTransport Policy
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An association model for bivariate data with application to the anlysis of university students' success.

2015

The academic success of students is a priority for all universities. We analyze the students' success at university by considering their performance in terms of both ‘qualitative performance’, measured by their mean grade, and ‘quantitative performance’, measured by university credits accumulated. These data come from an Italian University and concern a cohort of students enrolled at the Faculty of Economics. To jointly model both the marginal relationships and the association structure with covariates, we fit a bivariate ordered logistic model by penalized maximum likelihood estimation. The penalty term we use allows us to smooth the association structure and enlarge the range of possible …

Statistics and Probability05 social sciencesBivariate analysisLogistic regression01 natural sciencesTerm (time)010104 statistics & probabilityGoodness of fitBivariate data0502 economics and businessStatisticsCovariateEconometricsRange (statistics)Settore SECS-S/05 - Statistica Sociale050207 economics0101 mathematicsStatistics Probability and UncertaintyAssociation (psychology)Mathematicsmodels for association students' performance bivariate ordinal response Dale's model maximum penalized likelihood estimation
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Calibrating a microscopic traffic simulation model for roundabouts using genetic algorithms

2018

The paper introduces a methodological approach based on genetic algorithms to calibrate microscopic traffic simulation models. The specific objective is to test an automated procedure utilizing genetic algorithms for assigning the most appropriate values to driver and vehicle parameters in AIMSUN. The genetic algorithm tool in MATLAB® and AIMSUN micro-simulation software were used. A subroutine in Python implemented the automatic interaction of AIMSUN with MATLAB®. Focus was made on two roundabouts selected as case studies. Empirical capacity functions based on summary random-effects estimates of critical headway and follow up headway derived from meta-analysis were used as reference for ca…

Statistics and Probability050210 logistics & transportationGenetic algorithm traffic microsimulation AIMSUN passenger car equivalent roundaboutComputer science05 social sciencesReal-time computingGeneral EngineeringTraffic simulation02 engineering and technologySettore ING-INF/04 - AutomaticaArtificial Intelligence0502 economics and business0202 electrical engineering electronic engineering information engineeringSettore ICAR/04 - Strade Ferrovie Ed Aeroporti020201 artificial intelligence & image processingJournal of Intelligent & Fuzzy Systems
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Random walks in dynamic random environments and ancestry under local population regulation

2015

We consider random walks in dynamic random environments, with an environment generated by the time-reversal of a Markov process from the oriented percolation universality class. If the influence of the random medium on the walk is small in space-time regions where the medium is typical, we obtain a law of large numbers and an averaged central limit theorem for the walk via a regeneration construction under suitable coarse-graining. Such random walks occur naturally as spatial embeddings of ancestral lineages in spatial population models with local regulation. We verify that our assumptions hold for logistic branching random walks when the population density is sufficiently high.

Statistics and Probability82B43Markov processRandom walklogistic branching random walk01 natural sciences60K37 60J10 60K35 82B43010104 statistics & probabilitysymbols.namesakeMathematics::ProbabilityFOS: MathematicsLocal populationStatistical physics0101 mathematicsoriented percolationCentral limit theoremMathematicsdynamical random environmentProbability (math.PR)010102 general mathematicsRandom mediaRenormalization groupsupercritical clusterRandom walk60K37Population model60K35central limit theorem in random environmentPercolationsymbols60J10Statistics Probability and UncertaintyMathematics - ProbabilityElectronic Journal of Probability
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A penalized approach for the bivariate ordered logistic model with applications to social and medical data

2018

Bivariate ordered logistic models (BOLMs) are appealing to jointly model the marginal distribution of two ordered responses and their association, given a set of covariates. When the number of categories of the responses increases, the number of global odds ratios to be estimated also increases, and estimation gets problematic. In this work we propose a non-parametric approach for the maximum likelihood (ML) estimation of a BOLM, wherein penalties to the differences between adjacent row and column effects are applied. Our proposal is then compared to the Goodman and Dale models. Some simulation results as well as analyses of two real data sets are presented and discussed.

Statistics and ProbabilityAssociation (object-oriented programming)05 social sciencesDale modelBivariate analysisLogistic regression01 natural sciencesbivariate ordered logistic modelSet (abstract data type)010104 statistics & probabilityordinal associationpenalized maximum likelihood estimation0502 economics and businessStatisticsCovariateDale model bivariate ordered logistic model penalized maximum likelihood estimation ordinal associationSettore SECS-S/05 - Statistica Sociale0101 mathematicsStatistics Probability and UncertaintyMarginal distributionSettore SECS-S/01 - Statistica050205 econometrics MathematicsOrdinal association
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Correcting for non-ignorable missingness in smoking trends

2015

Data missing not at random (MNAR) is a major challenge in survey sampling. We propose an approach based on registry data to deal with non-ignorable missingness in health examination surveys. The approach relies on follow-up data available from administrative registers several years after the survey. For illustration we use data on smoking prevalence in Finnish National FINRISK study conducted in 1972-1997. The data consist of measured survey information including missingness indicators, register-based background information and register-based time-to-disease survival data. The parameters of missingness mechanism are estimable with these data although the original survey data are MNAR. The u…

Statistics and ProbabilityBackground informationFOS: Computer and information sciencesta112Test data generationComputer scienceSurvey samplingnon-participationta3142Smoking prevalenceBayesian inferenceMissing dataStatistics - Applicationsregistry dataMethodology (stat.ME)missing dataStatisticsSurvey data collectionRegistry dataApplications (stat.AP)Statistics Probability and Uncertaintysurvey samplingStatistics - Methodologysmoking prevalencehealth examination survey
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Cluster-Localized Sparse Logistic Regression for SNP Data

2012

The task of analyzing high-dimensional single nucleotide polymorphism (SNP) data in a case-control design using multivariable techniques has only recently been tackled. While many available approaches investigate only main effects in a high-dimensional setting, we propose a more flexible technique, cluster-localized regression (CLR), based on localized logistic regression models, that allows different SNPs to have an effect for different groups of individuals. Separate multivariable regression models are fitted for the different groups of individuals by incorporating weights into componentwise boosting, which provides simultaneous variable selection, hence sparse fits. For model fitting, th…

Statistics and ProbabilityBoosting (machine learning)Computer scienceMultivariable calculusComputational BiologyHigh-Throughput Nucleotide SequencingFeature selectionRegression analysisModels TheoreticalLogistic regressioncomputer.software_genrePolymorphism Single NucleotideRegressionComputational MathematicsLogistic ModelsData Interpretation StatisticalGeneticsCluster AnalysisHumansData miningCluster analysisMolecular BiologyUnit-weighted regressioncomputerGenome-Wide Association StudyStatistical Applications in Genetics and Molecular Biology
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